Abstract

Ulcerative colitis (UC), a chronic inflammatory disease of the colon with unknown etiology, is characterized by remission and recurrence. At present, a considerable number of UC cases are misdiagnosed or delayed in diagnosis and treatment. We aimed to identify UC-related genes to aid the development of drugs for this condition. Transcriptome data of 362 patients with UC and 126 control subjects were obtained from the Gene Expression Omnibus. The 362 patients with UC were subgrouped using unsupervised machine learning. R software was used to analyze the clinical characteristics of the subgroups, screen subgroup-specific genes, assess the relationships between gene modules and clinical characteristics using weighted gene co-expression network analysis, and perform Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of the subgroups. Patients with UC were classified into two subgroups. Genes specific to subgroup I included IL21R, ATP8B2, and PLEKHO1. Severe disease tended to be associated with immune cell infiltration; anti-tumor necrosis factor (TNF)-α antibodies and ustekinumab may have been effective in this subgroup. Subgroup II-specific genes included SLC4A4, EPB41L4B, and PLCE1. Patients in this subgroup had mild clinical conditions; however, their disease was more likely to progress to colorectal cancer. Thus, 5-aminosalicylic acid-based drugs may be effective for the treatment of UC in these patients. We divided UC into two molecular subgroups based on transcriptome data, providing molecular evidence for the development of diagnostic methods and individualized treatment strategies for UC.

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